1. Field of the Invention
The present invention relates generally to the field of electrical power systems. More specifically, the present invention discloses a neural network power distribution control element for a phased array antenna and similar distributed systems.
2. Statement of the Problem
Conventional space-borne phased array antennas, communication satellites and signal intelligence satellites currently use large solar arrays, heavy battery assemblies, and complex power distribution systems to operate. Large-area phased array antennas require enormous power to function. They tend to be heavy because of the area required by hundreds of thousands of radiator elements needed to accomplish the mission. Typically multiples of radiator elements are combined onto a single transmit/receive (TR) module and multiple TR modules are combined into a radio frequency (RF) tile, which provides a convenient building block with which to work. Ideally, each TR module is driven from a low voltage current (i.e., 3 to 4 volts).
Present power systems for such phased array antennas collect energy though the solar panels that is sent to a central voltage regulator and power conditioner from which large-capacity batteries (usually multiple 60 to 200 amp-hour) are charged. The batteries supply power to the bus and payload through a power distribution unit, typically at 28 volts. The voltage at the RF tiles is dropped to significantly lower levels through a voltage de-boost circuit that distributes the power to the TR modules. There are significant losses inherent to the cumulative inefficiencies associated with all of the steps from the solar collection to the TR modules.
For example, standard power systems for such phased array antennas use nickel-hydrogen or nickel-cadmium batteries, both of which have significant drawbacks associated with them, including life limitations due to depth of discharge, heavy packaging constraints, and reconditioning requirements. Lithium-ion batteries are a promising technology because they offer much lighter, more efficient assemblies. Several limitations stand in the way of their development. The individual cells don""t interact well together and require separate charge controls. For 60 to 200 amp-hour battery assemblies, significant challenges in charge control, thermal dissipation, cell scalability and other technical problems face battery engineers. Also, in order to achieve long life from each battery (i.e., 50,000 cycles) the depth of discharge has to be limited to less than 10 percent, meaning that the overall size of battery becomes too large to take advantage of the high energy density ratio that Li-ion technology offers. Substantial research and development efforts have been dedicated to overcoming these deficiencies.
Solar energy can be converted into electricity by means of solar cells composed of various chemistries. One of the most efficient solar cell technologies is galium-arsenide dual junction, which can be as good as 25% efficient and development efforts promise 30% efficiencies in the near future. However, they are susceptible to degradation from radiation and require cover slides for protection, thus adding weight to the solar array. Furthermore, the cells within each string are connected in series which boosts the voltage to a higher level. The strings are then connected in parallel to send current from the solar array to the regulator, conditioner and battery through a heavy wire bundle. The fact that strings are wired in series results in the loss of an entire string should a single cell be lost due to cell failure, broken connection, shadow, etc.
3. Solution to the Problem
The present invention addresses many of the shortcomings associated with conventional power distribution systems for phased array antennas. The present system provides current directly from solar cells to lithium-ion battery cells through a charge control regulated by a neural network at each battery. The small current required to operate each TR module is provided by an adjacent battery, rather than a large centralized battery assembly located on the spacecraft bus.
This approach eliminates the need for the majority of power distribution components that are traditionally used to operate phased array antennas. This technology eliminates or replaces heavy components such as voltage regulators, power distribution units and wire harnesses with significantly lighter, less complex elements. It allows for small currents and small voltages to provide power to the TR modules avoiding loss due to long cable runs. It enables the use of lithium-ion cells that have much higher energy density ratios by eliminating the technological problems that are associated with large capacity lithium-ion battery assemblies. Use of lithium-ion technology represents about a 70% cost reduction in battery assemblies. The incorporation of a neural network charge controller increases battery life and eliminates the need for thousands of lines of software code and computations. This idea will yield significant improvements in costs associated with manufacturing, assembly and testing. Less efficient but much lighter and much less expensive solar cells such as copper indium diselenide (CIS) or amorphous silicon fabricated on an Upilex(copyright) mylar substrate to be used in conjunction with this concept offering further weight and cost savings and both contribute greatly to long life and graceful degradation of the payload.
This revolutionary approach can be used to reduce the weight and cost of any phased array space-borne antenna system. Also any electronic system requiring small voltages distributed over large areas would be potential candidates for utilizing this technology.
The present invention significantly improves the efficiency by which solar energy is distributed and controlled to large phased array antenna assemblies. By providing current directly from solar cells to lithium-ion battery cells through a neural network, charge control is accomplished at each battery using a microprocessor. The small current required to operate each TR module is provided from an adjacent battery cell rather than a large centralized battery assembly located in the spacecraft bus. In the preferred embodiment, the charge control is regulated by a back-propagation neural network.